PARALLEL DYNAMIC AGGREGATION SYSTEM AND METHOD

Aggregation of data and subsequent diving and/or grouping (i.e., slicing and dicing) of the aggregated data occurs by multi-stage parallel processing. Initially, multiple aggregation jobs are executed in parallel to aggregate data from a granular level to a higher level. Subsequently, query sets are executed in parallel for each of the aggregation jobs to divide and/or group the higher level data according to the queries and the segregated results are stored in a single table, which is partitioned for each aggregation job. Parallel processing of the query sets and storage in a single table is made possible by implementing a hybrid dynamic database schema, in which each table in the database includes one or more additional fields, each additional field comprising a set of dimension-dimension value pairs.